Genetic Algorithm Based Aerodynamic Shape Optimization Tool for Wind Turbine Blades and its Implementation to Helicopters

Date

2014-05-22

Author

Tonkal, Ozan Çağrı
Pehlivan, Sercan
Sezer Uzol, Nilay
İşler, Veysi

Metadata

Show full item record

Item Usage Stats

34
views

0
downloads

URI

https://hdl.handle.net/11511/83632

Collections

Unclassified, Article

Suggestions

OpenMETU
Core

Genetic Algorithm based aerodynamic shape optimization tool for wind turbine blades and its implementation to helicopter blades Polat, Özge; Sezer-uzol, Nilay; Tuncer, İsmail Hakkı (2014-01-01) This study presents a methodology first built up for the aerodynamic shape optimization for wind turbine rotors and its modified version for a helicopter rotor in hover. The Genetic Algorithm (GA) coupled with an in-house Blade Element Momentum (BEM) tool is used in the design optimization process. The wind turbine blade optimization studies are performed for maximizing the power production at a given wind speed, rotor speed and rotor diameter, while for the helicopter blade optimization in hover, figure of...
Genetic algorithm based aerodynamic shape optimization of wind turbine rotor blades using a 2-d panel method with a boundary layer solver Polat, Özge; Tuncer, İsmail Hakkı; Sezer Uzol, Nilay; Department of Aerospace Engineering (2011) This thesis presents an aerodynamic shape optimization methodology for rotor blades of horizontal axis wind turbines. Genetic Algorithm and Blade Element Momentum Theory are implemented in order to find maximum power production at a specific wind speed, rotor speed and rotor diameter. The potential flow solver, XFOIL, provides viscous aerodynamic data of the airfoils. Optimization variables are selected as the sectional chord length, the sectional twist and the blade profiles at root, mid and tip regions of...
Genetic algorithm for constrained optimization models and its application in groundwater resources management Guan, Jiabao; Kentel Erdoğan, Elçin; Aral, Mustafa M. (American Society of Civil Engineers (ASCE), 2008-01-01) Genetic algorithms (GAs) have been shown to be an efficient tool for the solution of unconstrained optimization problems. In their standard form, GA formulations are "blind" to the constraints of an optimization model when the model involves these constraints. Thus, in GA applications alternative procedures are used to satisfy the constraints of the optimization model. In this study, the method that is utilized in the Complex Algorithm to solve constrained optimization problems is abstracted to develop a re...
Genetic algorithm for estimating multiphase flow functions from unsteady-state displacement experiments Akın, Serhat (1998-04-30) Relative permeability and capillary pressure are the primary flow parameters required to model multiphase flow in porous media. Frequently, these properties are estimated on the basis of unsteady state laboratory displacement experiments. Interpretation of the flood process to obtain relative permeability data is performed by one of two means: application of frontal advance theory or direct computer simulation. Application of frontal advance theory requires a number of experimental restrictions such that th...
Genetic algorithm approach for the optimization of technical trading rule parameters. Hülagü, Timur; Selçuk, Sevtap; Department of Statistics (2001)

Citation Formats

O. Ç. Tonkal, S. Pehlivan, N. Sezer Uzol, and V. İşler, “Genetic Algorithm Based Aerodynamic Shape Optimization Tool for Wind Turbine Blades and its Implementation to Helicopters,” 2014, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/83632.